QueenLiz-120B-GGUF / README.md
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metadata
exported_from: Noodlz/QueenLiz-120B
language:
  - en
library_name: transformers
quantized_by: mradermacher

About

static quants of https://huggingface.co/Noodlz/QueenLiz-120B

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q2_K 44.6
PART 1 PART 2 Q3_K_S 52.2
PART 1 PART 2 IQ3_S 52.4 beats Q3_K*
PART 1 PART 2 Q3_K_M 58.2 lower quality
PART 1 PART 2 Q3_K_L 63.4
PART 1 PART 2 Q4_0 68.2
PART 1 PART 2 Q4_K_S 68.7 fast, recommended
PART 1 PART 2 Q4_K_M 72.6 fast, recommended
PART 1 PART 2 Q5_K_S 83.2
PART 1 PART 2 Q5_K_M 85.4
PART 1 PART 2 PART 3 Q6_K 99.1 very good quality
PART 1 PART 2 PART 3 Q8_0 128.2 fast, best quality

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.